Chromogenic staining techniques have been developed empirically to impart visual contrast to various elements within tissue samples. Staining techniques and protocols can produce mixtures of dyes in different tissue elements, and human observers, using microscopes and other imaging devices, have learned to distinguish these staining patterns as typical for particular elements. Modern targeted staining methods, which can be specific to chemical moieties and/or molecular structural arrangements, can produce stained tissues in which two or more chromogenic or fluorescent stains apparently overlap spatially. In fact, the perceived overlap can result because the multiple stains truly are bound within a common structure in the sample, or because, due to the method of preparation, a structure within the sample containing one stain overlaps with a second structure containing a different stain. In either case, it may be difficult to distinguish the presence and relative distribution of the multiple stains and the structures to which they are bound, especially when the stains employed have similar spectral absorption and/or emission characteristics.
In fields such as pathology and cytology in which staining and inspection of tissue samples occurs frequently, the stained samples are often classified according to one or more criteria by human researchers performing visual inspection of the samples using a microscope or other imaging device. For example, a sample can be stained with multiple dyes in order to highlight differences in particular organelles, structures, or molecular targets among cells in the sample. Samples containing different types of cells can be treated with different dyes in order to visually distinguish the number, spatial distribution, and morphology of the cell types. The samples can then be classified according to one or more criteria such as the presence of different types of chemical or biological structures therein. A wide variety of staining protocols have been developed in order to provide different types of classification information for particular classes of samples.
As an alternative to the sometimes tedious procedure of manual inspection and classification of tissue samples, machine-vision methods can be employed in an effort to automate the process of sample classification.